Initialization¶

Load data¶

load_raw_eeg() from_mne_epochs()

'load_epochs' load_dataframe_pickle() load_dataframe_hdf5(files=[],path='',subjIDs=[],montage_path='standard-10-5-cap385',compress=False) load_mne_fif() load_eeglab_mat() load_filetrip_mat() todo

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Extract the data¶

epochs = Epochs(all,average,info)

epochs.save(self, filepath, append=False)

extracted = epochs.extract(collection_script, average=False)

extracted.get_batch_names(self, batch_id='all') extracted.get_dataframe(self, batch_id=0, case_id=0, to_print=False) extracted.get_array(self, batch_id=0, case_id=0, to_print=False) extracted.get_index(self, batch_id=0, case_id=0, to_print=False) extracted.get_info(self, key)

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Analysis¶

structure.Extracted_epochs.ERP() structure.Extracted_epochs.topo_ERPs() structure.Extracted_epochs.ERPs() structure.Extracted_epochs.RMS() structure.Extracted_epochs.Spectrum() structure.Extracted_epochs.Time_frequency() structure.Extracted_epochs.topography() structure.Extracted_epochs.significant_channels_count() structure.Extracted_epochs.clustering() structure.Extracted_epochs.TANOVA() structure.Extracted_epochs.classification()

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Plot¶

plot(self, plot_params=None, save=False, return_fig=False)

'figure_group' float_plot(fig, data, annotation, positions, plot_params) matrix_plot(fig, data, annotation, x_axis, y_axis, plot_params)

'figure_unit' plot_waveform(ax, data, plot_params) plot_spectrum(ax, data, plot_params) plot_heatmap(ax, data, plot_params) plot_topograph(ax, data, plot_params) channel_locs(topo)